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Gaussian Processes from First Principles

Source: R/gaussianprocesses-package.R
gaussianprocesses-package.Rd

gaussianprocesses provides mathematically explicit implementations of Gaussian-process models with an emphasis on numerical stability, uncertainty quantification, and reproducibility. The mathematical vignettes map each model equation to the corresponding package objects.

Stability and versioning

Every exported function belongs to one of three tiers, which its help page states in a "Stability" section and by which the reference index on the package website is grouped.

  • Stable. From version 1.0.0, a stable interface changes incompatibly only in a major release. A stable function, argument, or result field that is replaced is first deprecated: it keeps working with a warning for at least one minor release, and is removed in the next major release.

  • Experimental. An experimental interface may change in a minor release, and every change is listed in NEWS. The experimental interfaces are the sparse approximations, latent models with their likelihoods and scores, the heteroscedastic method, state-space inference, the spectral-mixture and changepoint kernels, derivative observations and gradient prediction, hyperparameter uncertainty, the numerical and calibration diagnostics, and the benchmark and simulation-scenario helpers.

  • Deprecated. A deprecated name warns when used and will be removed in the next major release. Version 1.0.0 has no deprecated names.

Results and options of a stable function that concern an experimental model class, kernel, or argument follow the experimental tier: for example, predict_gp() is stable, but its behaviour for a state-space model is as experimental as state-space inference.

Version numbers follow semantic versioning from 1.0.0. A major release may change stable interfaces incompatibly; a minor release adds features and may change experimental interfaces; a patch release only fixes defects compatibly.

Fitted models record the format version they were saved with (see gaussianprocesses_model). Every 1.x release reads models saved by any earlier release, back to 0.1.0.

See also

Useful links:

Author

Maintainer: Diogo Ribeiro dfr@esmad.ipp.pt (ORCID) (Faculty of Media Arts and Design of the Technical University of Porto)